Knowledge Hub

Autonomous Database: The transformational approach to Database Management (Part 1)

Share on facebook
Share on twitter
Share on linkedin
Share on email
Share on whatsapp
Autonomous Database

There has been a lot of buzz about “Autonomous Database”. Let us understand what an autonomous database is and compare it with traditional databases that most enterprises use.

An autonomous database is a cloud database which is equipped with artificial intelligence and machine learning capabilities. Such databases can use machine learning to perform database tuning, ensure database security and updates and perform regular back-ups and routine database management tasks all by itself. The autonomous database can perform the above-mentioned activities without the assistance or intervention of a database administrator or a database management professional.

The need for an Autonomous Database

Enterprise Databases store the most critical and sensitive information about a company, its customers, and employees. They are the robust foundations which host the enterprise data. This data, in turn, enables applications to derive insights, reports etc. and enable processes to enhance strategic decision making, customer experience etc.

In the digital age, factors such as global internet coverage and penetration, cost-effective network, compute and storage resources via the cloud, and a multitude of access points (devices) has led to a huge proliferation of data itself. A database administrator (DBA) or even a team of DBAs will find it increasingly difficult and demanding to manage prolific workloads. This will result in errors which impact not only the performance of databases but also compromise the security and sanctity of data and reputation of the company.

The data deluge makes it extremely difficult for DBAs to manage the databases, ensure its security and consistently tune its performance. The databases, thus, often run at full capacity, process requests at a very slow pace or become unavailable. This could lead to non-responsive or slow application performance which leads to frustrated customers and loss of business. It also leads to unhappy employees and loss of productivity and efficiency.

An autonomous database can take over the functions of update, repair, and management to a certain extent on itself. With no human intervention required, it can release the bandwidth of skilled IT talent that can be deployed across much more productive, analytical, and strategic work.

What are the constituents of an Autonomous Database?

An autonomous database comprises a Data Warehouse and Transaction Processing.

The data warehouse of an autonomous database is equipped with pre-compute capabilities to ensure that data across millions of rows is ready for analysis and results can be derived in seconds.

Transaction processing enables real-time transaction analysis, ensures tailor-made experiences and detection of anomalous transaction patterns.

Functioning of an Autonomous Database

With its capabilities to leverage artificial intelligence (AI) and machine learning, autonomous databases can seamlessly provision database resources, ensure security and updates, and enable high availability, performance, and prevention of errors all by itself. It does not require any human intervention whatsoever.

The key characteristics of an autonomous database are:

Self-Driving: An autonomous database can manage, monitor, and ensure performance tuning of the database all by itself. The DBAs can thus, focus on ensuring seamless connectivity of databases with applications. They can use their bandwidth to help developers to leverage the database and its features much better.

Self-Securing:  An autonomous database can ward off malicious attacks by ensuring a level of security against cyberattacks which make databases, especially the unpatched and unencrypted ones, very vulnerable.

Self-Repairing: These databases can install patches and upgrades on its own. Thus, it can drastically bring down the downtime and planned maintenance related interruptions. As per Oracle, its autonomous database requires less than 2.5 minutes per downtime to repair itself and ensure that the latest patches have been applied.

Benefits of Autonomous Database

While there are innumerable benefits, the three key benefits are as below:

Performance: The Cloud based Autonomous Database ensures that the databases are up and running virtually 24*7*365. In addition to database uptime, it ensures seamless performance and enhanced security while also ensuring automatic patching and fixes.

Productivity: These databases enhance the productivity of DBAs to the maximum. They also ensure that unnecessary manual errors, which can impact the organization’s business and reputation significantly, are eliminated as the management of databases is automated.  

Cost-effectiveness: By automating routine tasks, the autonomous databases reduce cost and improve productivity.

Autonomous Databases are cloud-based and can offer a plethora of advantages. Many organizations are considering the positive impact that it can have on overall application development and availability, business acceleration and customer engagement.

In the upcoming blogs on Autonomous Databases, we will look at a few more important aspects to give a broader perspective of why they must be an integral part of your infrastructure modernization strategy.

Also Read: Autonomous Database (Part 2) – Accelerating Application Development and “Go-to-Market”

Leave a comment

Your email address will not be published. Required fields are marked *

Subscribe to Our Blog

Stay updated with the latest trends in the field of IT

Before you go...

We have more for you! Get latest posts delivered straight to your inbox